fix unittest for ccd Effect model

tests/det_effect_unit_test.py

@@ -6,18 +6,28 @@ import matplotlib.pyplot as plt
 import os,sys,math,copy
 from numpy.random import Generator, PCG64
 import warnings
+from astropy.io import fits
 
 warnings.filterwarnings("ignore", '.*Numba.*',)
 
 width = 9216
 height = 9232
 
-if os.path.isdir('./output/'):
-    pass
-else:
-    os.mkdir('./output/')
-
 class DetTest(unittest.TestCase):
+
+    def __init__(self, methodName='runTest'):
+        super(DetTest,self).__init__(methodName)
+        self.filePath('csst_fz_gc0')
+
+    def filePath(self, file_name):
+        self.datafn = os.path.join(os.getenv('UNIT_TEST_DATA_ROOT'), file_name)
+        self.outDataFn = os.path.join(self.datafn,'output')
+        if os.path.isdir(self.outDataFn):
+            pass
+        else:
+            os.mkdir(self.outDataFn)
+        
+
     def test_prnu(self):
         '''
         Unit test for PRNU. Expected result: a randomized GS image contains PRNU with sigma=0.01, mean=1.
@@ -64,12 +74,12 @@ class DetTest(unittest.TestCase):
         img.addNoise(galsim.GaussianNoise(sigma=7))
         # plt.imshow(img.array)
         # plt.show()
-        filename1 = os.path.join('output','test_satu_initimg.fits')
+        filename1 = os.path.join(self.outDataFn,'test_satu_initimg.fits')
         img.write(filename1)
         newimg = Effects.SaturBloom(img, fullwell=9e4)
         # plt.imshow(newimg.array)
         # plt.show()
-        filename2 = os.path.join('output','test_satu_bleedimg.fits')
+        filename2 = os.path.join(self.outDataFn,'test_satu_bleedimg.fits')
         newimg.write(filename2)
         del img,newimg, star
 
@@ -79,16 +89,16 @@ class DetTest(unittest.TestCase):
         '''
         imgarr = np.arange(1,9e4,4).reshape((150,150))
         img = galsim.Image(copy.deepcopy(imgarr))
-        filename1 = os.path.join('output','test_nonlinear_initimg.fits')
+        filename1 = os.path.join(self.outDataFn,'test_nonlinear_initimg.fits')
         img.write(filename1)
         newimg = Effects.NonLinearity(img, beta1=5E-7, beta2=0)
-        filename2 = os.path.join('output','test_nonlinear_finalimg.fits')
+        filename2 = os.path.join(self.outDataFn,'test_nonlinear_finalimg.fits')
         newimg.write(filename2)
         plt.scatter(imgarr.flatten(), newimg.array.flatten(), s=2, alpha=0.5)
         plt.plot([-1e3,9e4],[-1e3,9e4],color='black', lw=1, ls='--')
         plt.xlabel('input (e-)')
         plt.ylabel('output (e-)')
-        plt.savefig('./output/test_nonlinearity.png', dpi=200)
+        plt.savefig(os.path.join(self.outDataFn,'test_nonlinearity.png'), dpi=200)
         plt.show()
         del img,newimg,imgarr
 
@@ -97,35 +107,35 @@ class DetTest(unittest.TestCase):
         rgbadpix = Generator(PCG64(20210911))
         badfraction = 5E-5*(rgbadpix.random()*0.5+0.7)
         img = Effects.DefectivePixels(img, IfHotPix=True, IfDeadPix=True, fraction=badfraction, seed=20210911, biaslevel=0)
-        img.write('./output/test_badpixel_HtrDtr.fits')
+        img.write(os.path.join(self.outDataFn,'test_badpixel_HtrDtr.fits'))
         del img
     def test_badpixel_HfsDtr(self):
         img = galsim.Image(500,500,init_value=1000)
         rgbadpix = Generator(PCG64(20210911))
         badfraction = 5E-5*(rgbadpix.random()*0.5+0.7)
         img = Effects.DefectivePixels(img, IfHotPix=False, IfDeadPix=True, fraction=badfraction, seed=20210911, biaslevel=0)
-        img.write('./output/test_badpixel_HfsDtr.fits')
+        img.write(os.path.join(self.outDataFn,'test_badpixel_HfsDtr.fits'))
         del img
     def test_badpixel_HtrDfs(self):
         img = galsim.Image(500,500,init_value=1000)
         rgbadpix = Generator(PCG64(20210911))
         badfraction = 5E-5*(rgbadpix.random()*0.5+0.7)
         img = Effects.DefectivePixels(img, IfHotPix=True, IfDeadPix=False, fraction=badfraction, seed=20210911, biaslevel=0)
-        img.write('./output/test_badpixel_HtrDfs.fits')
+        img.write(os.path.join(self.outDataFn,'test_badpixel_HtrDfs.fits'))
         del img
     def test_badpixel_HfsDfs(self):
         img = galsim.Image(500,500,init_value=1000)
         rgbadpix = Generator(PCG64(20210911))
         badfraction = 5E-5*(rgbadpix.random()*0.5+0.7)
         img = Effects.DefectivePixels(img, IfHotPix=False, IfDeadPix=False, fraction=badfraction, seed=20210911, biaslevel=0)
-        img.write('./output/test_badpixel_HfsDfs.fits')
+        img.write(os.path.join(self.outDataFn,'test_badpixel_HfsDfs.fits'))
         del img
 
     def test_badlines(self):
         img = galsim.Image(500,500,init_value=-1000)
         img.addNoise(galsim.GaussianNoise(sigma=7))
         newimg = Effects.BadColumns(copy.deepcopy(img), seed=20210911)
-        newimg.write('./output/test_badlines.fits')
+        newimg.write(os.path.join(self.outDataFn,'test_badlines.fits'))
         del newimg,img
 
     def test_cte(self):
@@ -134,8 +144,8 @@ class DetTest(unittest.TestCase):
         img.array[150,150] = 3e4
         newimgcol = Effects.CTE_Effect(copy.deepcopy(img),direction='column')
         newimgrow = Effects.CTE_Effect(copy.deepcopy(img),direction='row')
-        newimgcol.write('./output/test_ctecol.fits')
-        newimgrow.write('./output/test_cterow.fits')
+        newimgcol.write(os.path.join(self.outDataFn,'test_ctecol.fits'))
+        newimgrow.write(os.path.join(self.outDataFn,'test_cterow.fits'))
         del img,newimgcol,newimgrow
 
     def test_readnoise(self):
@@ -144,7 +154,7 @@ class DetTest(unittest.TestCase):
         rng_readout = galsim.BaseDeviate(seed)
         readout_noise = galsim.GaussianNoise(rng=rng_readout, sigma=5)
         img.addNoise(readout_noise)
-        img.write('./output/test_readnoise.fits')
+        img.write(os.path.join(self.outDataFn,'test_readnoise.fits'))
         stdval = np.std(img.array)
         self.assertTrue(np.abs(stdval-5)<0.01*5)
         print('\nUnit test for readout noise has been passed.')
@@ -158,8 +168,8 @@ class DetTest(unittest.TestCase):
 
     def test_apply16gains(self):
         img = galsim.Image(500,500,init_value=100)
-        img = Effects.ApplyGainNonUniform16(img, gain=1.5, nsecy=2, nsecx=8, seed=202102)
-        img.write("./output/test_apply16gains.fits")
+        img,_ = Effects.ApplyGainNonUniform16(img, gain=1.5, nsecy=2, nsecx=8, seed=202102)
+        img.write(os.path.join(self.outDataFn,'test_apply16gains.fits'))
         rightedge = int(500/8)*8
         print('gain=%6.2f' % 1.5)
         meanimg = np.mean(img.array[:,:rightedge])
@@ -172,20 +182,20 @@ class DetTest(unittest.TestCase):
 
 
     def test_cosmicray(self):
-        attachedSizes = np.loadtxt('../ObservationSim/Instrument/Chip/wfc-cr-attachpixel.dat')
-        cr_map = Effects.produceCR_Map(
+        attachedSizes = np.loadtxt(os.path.join(self.datafn,'wfc-cr-attachpixel.dat'))
+        cr_map,_ = Effects.produceCR_Map(
                 xLen=500, yLen=500, exTime=150+0.5*40, 
                 cr_pixelRatio=0.003*(1+0.5*40/150), 
                 gain=1, attachedSizes=attachedSizes, seed=20210911)
         crimg = galsim.Image(cr_map)
-        crimg.write('./output/test_cosmicray.fits')
+        crimg.write(os.path.join(self.outDataFn,'test_cosmicray.fits'))
         del cr_map,crimg
 
     def test_shutter(self):
         img = galsim.Image(5000,5000,init_value=1000)
         shuttimg = Effects.ShutterEffectArr(img, t_exp=150, t_shutter=1.3, dist_bearing=735, dt=1E-3)    # shutter effect normalized image for this chip
         img *= shuttimg
-        img.write('./output/test_shutter.fits')
+        img.write(os.path.join(self.outDataFn,'test_shutter.fits'))
         del img
 
     def test_vignette(self):
@@ -195,7 +205,7 @@ class DetTest(unittest.TestCase):
         img.setOrigin(10000,10000)
         flat_img = Effects.MakeFlatSmooth(img.bounds,20210911)
         flat_normal = flat_img / np.mean(flat_img.array)
-        flat_normal.write('./output/test_vignette.fits')
+        flat_normal.write(os.path.join(self.outDataFn,'test_vignette.fits'))
         del flat_img,img,flat_normal
 
 

tests/testData/csst_fz_gc0/wfc-cr-attachpixel.dat

+# Graph from wfc-cr-attach, page 1
+0.00000	0.004684
+0.5031	0.004684
+0.5283	0.01873
+1.509	0.01873
+1.534	0.09327
+2.490	0.09327
+2.515	0.1034
+3.496	0.1034
+3.522	0.2440
+4.503	0.2440
+4.528	0.1107
+5.509	0.1107
+5.534	0.1013
+6.490	0.1013
+6.515	0.06090
+7.496	0.06090
+7.522	0.05834
+8.503	0.05834
+8.528	0.03875
+9.509	0.03875
+9.534	0.03066
+10.49	0.03066
+10.51	0.01788
+11.47	0.01788
+11.49	0.01831
+13.50	0.01831
+13.53	0.01235
+13.53	0.01235
+14.49	0.01235
+14.51	0.01064
+15.49	0.01064
+15.52	0.008091
+16.50	0.008091
+16.52	0.004684
+17.48	0.004684
+17.53	0.003833
+18.49	0.003833
+18.51	0.005536
+19.47	0.005536
+19.52	0.004684
+20.00	0.004684